FazBrowse GitHub Viewer
|
Trending
|
URL:
|
Home
Tools:
[Download Repo ZIP]
[View Raw Code]
[Original HTTPS Page]
Quantum_Computing_codingSchoolCourse/week9.py at main · SREEHARI1994/Quantum_Computing_codingSchoolCourse · GitHub
SREEHARI1994
/
Quantum_Computing_codingSchoolCourse
Public
Notifications
You must be signed in to change notification settings
Fork
0
Star
3
Code
Issues
0
Pull requests
0
Actions
Projects
Security and quality
0
Insights
Additional navigation options
Code
Issues
Pull requests
Actions
Projects
Security and quality
Insights
Expand file tree
Breadcrumbs
Quantum_Computing_codingSchoolCourse
/
week9.py
Copy path
More file actions
More file actions
Latest commit
History
History
History
94 lines (88 loc) · 2.41 KB
Breadcrumbs
Quantum_Computing_codingSchoolCourse
/
week9.py
Copy path
File metadata and controls
94 lines (88 loc) · 2.41 KB
Raw
Copy raw file
Download raw file
Open symbols panel
Edit and raw actions
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
from
week4
import
matrix_multiply
def
calculate_determinant4_2D
(
*
m
):
"""
Calculates and returns the determinants of a two by two real matrix.
Arguments can be passed as either two (2 X 1) vectorsi.e 2 python 1D lists
or as a single matrix of dim 2 X 2 or As a single 2D python list.
"""
if
len
(
m
)
==
2
:
matrix
=
[
m
[
0
],
m
[
1
]]
else
:
matrix
=
m
[
0
]
return
(
matrix
[
0
][
0
]
*
matrix
[
1
][
1
]
-
matrix
[
0
][
1
]
*
matrix
[
1
][
0
])
def
check4_linearIndependence
(
a
,
b
):
"""
It works on the principal that if the matrix formed by
the two vectors a and b passed here as columns has a non zero determinant, then
the vectors are linearly independent
"""
if
calculate_determinant4_2D
(
a
,
b
)
==
0
:
return
False
else
:
return
True
def
check_span_inR2
(
a
,
b
):
"""
Takes in 2 vectors as arguments and finds out if the
vectors spans R2 by checking if the determinant of the
resulting matrix is non-zero. Refer-
https://ltcconline.net/greenl/courses/203/Vectors/linIndSpan.htm
"""
if
calculate_determinant4_2D
(
a
,
b
)
==
0
:
return
False
else
:
return
True
def
eigen_equation
(
a
,
b
):
"""
Takes in two matrix a and eigen vector b, multiplies them
using matrix_multiply from week4.py. Then lambda X first value of
product vector = first value of b is used to calculate eigen value
lambda by doing division. Note product vector is returned
as a 2d list consisting of two single lists having only one element
and also that b is passed in as a 2d list
"""
product_vector
=
[]
result
=
matrix_multiply
(
a
,
b
)
product_vector
.
append
(
result
[
0
][
0
])
product_vector
.
append
(
result
[
1
][
0
])
eigen_value
=
product_vector
[
0
]
/
b
[
0
][
0
]
return
eigen_value
if
__name__
==
"__main__"
:
print
(
"1 True"
)
print
(
"2 True"
)
print
(
"3 False"
)
print
(
"4 True"
)
print
(
"5 b"
)
print
(
"6 a"
)
print
(
"7 a"
)
print
(
"8 b"
)
#print(calculate_determinant4_2D([1,0],[0,1]))
#print(calculate_determinant4_2D([[1,2],[3,4]]))
print
(
"9"
,
check4_linearIndependence
([
1
,
0
],[
0
,
1
]))
print
(
"10"
,
check4_linearIndependence
([
1
,
2
],[
3
,
6
]))
print
(
"11"
,
check4_linearIndependence
([
3
,
4
],[
7
,
1
]))
print
(
"12"
,
check_span_inR2
([
1
,
3
],[
2
,
1
]))
print
(
"13"
,
check_span_inR2
([
2
,
8
],[
1
,
4
]))
print
(
"14"
,
check_span_inR2
([
5
,
5
],[
1
,
1
]))
print
(
"15"
,
eigen_equation
([[
1
,
4
],[
0
,
5
]],[[
1
,
1
]]))
print
(
"16"
,
eigen_equation
([[
7
,
0
],[
3
,
4
]],[[
-
1
,
1
]]))
print
(
"17"
,
eigen_equation
([[
7
,
-
1
],[
2
,
4
]],[[
0.5
,
1
]]))
exit
()
"""
1 True
2 True
3 False
4 True
5 b
6 a
7 a
8 b
9 True
10 False
11 True
12 True
13 False
14 False
15 5.0
16 7.0
17 5.0
"""
Back
|
FazBrowse Home
|
New Git URL